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One of the types of objects in Praat. A DataModeler tries to fit N data points (xi, yi) as lying on a particular kind of model function f(x; p) that depends on M parameters p. The parameters p are determined by minimizing the chi squared function χ2(p)=Σ ((yi - f(xi, p))/σi)2, where the sum is over all N data points.
If the individual uncertainties σiof the data are not known before hand, the model parameter are determined by assuming that all uncertainties σi
are equal. However an independent assessment of the goodness-of-fit cannot be determined in this case. A good guess for σ2 for this case could be σ2=Σ (yi - f(xi, p))2.
© David Weenink, 2024